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Türkiye’deki Kamu Üniversitelerinde CCR Etkinliği-Ölçek Etkinliği Analizi: DEA Tekniği Uygulaması

Year 2008, Issue: 15, 148 - 172, 01.06.2008

Abstract

Bu çalışmada Kamu Üniversitelerinin göreli etkinlik ölçümleri VZA kullanılarak hesaplanmıştır. Girdi ve Çıktı Yönelimli olarak iki model kuruldu. Bu hesaplamada 53 devlet üniversitesi karar verme birimi olarak kullanıldı. Bu karar verme birimlerine ait gözlemlenmiş 8 girdi ve 6 çıktı kullanılarak analizler beş yıl için yapıldı. Hesaplamalar sonucunda beş yıl için etkin olan ve olmayan üniversiteler belirlendi. Üniversitelerin teknik ve ölçek etkinlikleri belirlendi. Bu çalışmada girdi yönelimli CCR modeline göre yapılan değerlendirmelere göre Türk Kamu Üniversitelerinde etkinsizlik gittikçe artmaktadır. Etkin olmayan üniversitelerin ölçek etkinlikleri hesaplandı. Bu hesaplar sonucunda beş yıl boyunca azalan, artan ve sabit ölçek özelliğine sahip üniversiteler tespit edildi. Girdi Yönelimli Modelde beş yıl içerisinde ÖSG özellikli üniversite sayısı 39’dan 29’a inmiş ÖAG özellikli üniversite sayısı 8’dan 17’a yükselmiş ve ÖAZG özellikli üniversite sayısı 6’dan 7’a yükselmiştir. Beş yıl üst üste 20 üniversite ise ÖSG; 2 üniversite ÖAG; 1 üniversite ÖAZG göstermiştir. Girdi Yönelimli Modelde üniversitelerin ölçek etkinliğini iyi kullanamadıkları görülmektedir. Ayrıca ölçek etkinsizliği her geçen yıl artmaktadır. Çıktı Yönelimli Modelde beş yıl içerisinde ÖSG özellikli üniversite sayısı 39’dan 29’a inmiş ÖAG özellikli üniversite sayısı 9’dan 22’a yükselmiş ve ÖAZG özellikli üniversite sayısı 5’dan 2’a azalmıştır. Beş yıl üst üste 20 üniversitede ÖSG; 2 üniversitede ÖAG hesaplanmıştır. ÖAZG gözlemlenmemiştir. Çıktı Yönelimli Modelde de üniversitelerin ölçek etkinliğini iyi kullanamadıkları görülmektedir. Çıktı Yönelimli Model çıktıların maksimizasyonu ile ilgilendiğinden dolayı ÖAG sayısı Çıktı Yönelimli Modelden beklenildiği gibi fazla çıkmaktadır

References

  • Ahn, T., 1987. Efficiency Related Issues in Higher Education: A Data Envelopment Analysis Approach, Ph.D. Thesis, The University of Texas at Austin.
  • Arcelus, F.J. and D.R. Coleman., 1995. “An Efficiency Review of University Departments,” Faculty of Administration, University of New Brunswick, mimeographed.
  • Athanassopoulos, A., Shale, Estelle., 1997. Assessing the comparative efficiency of higher education institutions in the UK by means of data envelopment analysis. Education Eco- nomics,5(2), 117–134.
  • Avkiran, Necmi K., 2001. Investigating technical and scale efficiencies of Australian Uni- versities through Data Envelopment Analysis. Socio-Economic PlanningSciences. 35, 57- 80.
  • Babacan, Adem, 2006. Türkiye’deki Üniversitelerde VZA Yöntemiyle Verimlilik Analizi. C.Ü. Sosyal Bilimler Enstitüsü. Doktora Tezi.
  • Chaparro F. Jimenez J, Smith P., 1997. On the Role of Weight Restrictions in Data Envel- opment Analysis. Journal of Productivity Analysis.8:215-230.
  • Coelli, Tim., 1996. Assessing the performance of Australian universities using data envel- opment analysis. Mimeo. Center for Efficiency and Productivity Analysis, University of New England
  • Cooper W.W, L.M Seiford, K. Tone., 1999. Data Envelopment Analysis. Kluwer Academic Publishers
  • Cooper W.W, L.M Seiford, J.Zhu, 2004. Handbook on Data Envelopment Analysis. Kluwer Academic Publishers
  • Dundar H, Darrell R. Lewis., 1995, Departmental productivity in American universities: Economies of scale and scope Economics of Education Review V.14, 2 P.119-144
  • Forsund Finn R.; Nikias Sarafoglou, 2002.On the Origins of Data Envelopment Analysis. Journal of Productivity Analysis, 17, 23–40.
  • Geraint Johnes, Jill Johnes , 1993. Measuring the Research Performance of UK Economics Departments: An Application of Data Envelopment Analysis Oxford Economic Papers, New Series, Vol. 45, No. 2, pp. 332-347
  • Jenkins, A.L. , 1991. Using Data Envelope Analysis to Evaluate the Relative Efficiency of Academic Departments, Royal Military College, Kingston, mimeo.
  • Kisaer H, Karabacakoğlu Ç., 2004. Çukurova Üniversitesi Diş Hekimliği Fak. Performans Analizi MPM No:679.
  • Kutlar A. Mahmut Kartal., 2004. Cumhuriyet Üniversitesinin Verimlilik Analizi: Fakülte Düzeyinde VZA Yöntemi ile Bir Uygulama. Kocaeli Üniversitesi Sosyal Bilimler Dergisi (8) 2: 49-79.
  • McMillan, M.L., Debasish D., 1997. The relative efficiencies of Canadian universities: a DEA perspective. Research paper No. 97-4, Department of Economics, University of Alberta.
  • Norman, M. Stoker. B. , 1991. Data Envelopment Analysis: The Assessment of Performance. John Wiley and Sons.
  • Sherman, H.D., 1984. “Data Envelopment Analysis as a New Manegerial Audit Methodology- Test and Evaluation”, Auditing: A Journal of Practice and Theory.
  • Susanne Warning, 2004. Performance Differences in German Higher Education: Empirical Analysis of Strategic Groups. Cetre for European Economic Reasearch. http://www.wiwi.uni-konstanz.de/forschergruppewiwi.
  • Thanassoulis E., 2001. Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with İntegrated Software, Kuluwer Academic Publisher
  • Tomkins, C. and R. Gren., 1988. An Experiment in the Use of Data Envelopment Analysis for Evaluating the Efficiency of UK University Departments of Accounting. Financial Accountability and Management 4: 147- 64.
  • Vassiloglou, M, Giokas, D., 1990. A Study of The Relative Efficiency of Bank Branches: An Application of Data Envelopment Analysis. Journal of Operational Research Society. 41: 591-597

A Comparison Of The Effectivity Of Cumhuriyet University With State Universities: An Applicatoin Of Dea Technique

Year 2008, Issue: 15, 148 - 172, 01.06.2008

Abstract

Abstract: In this study, the relative efficiency measures of the state Universities
are calculated by using DEA technique. Input and output oriented two models are
built. In these calculations 53 state universities were used as decision-making units.
Our analysis covers a 5-year period using 8 inputs and 6 outputs observed in these
decision-making units. As a result we have determined efficient and inefficient universities
in 5 years. Technical and scale efficiencies are determined. In accordance
with our assessments based on an input oriented CCR model, the inefficiency of the
Turkish state universities is progressively increasing. We have further calculated
the scale efficiencies of the inefficient universities, and determined which universities
show diminishing, increasing or stable scale characteristics during these 5
years. Based on the input oriented model, the number of universities with CRS characteristic
have decreased from 39 to 29, those with IRS have increased from 8 to
17 and those with DRS characteristic have increased from 6 to 7, within 5 years.
20 universities have shown CRS, 2 universities have shown IRS and one DRS in each
of these five years. It can be concluded that they were not able to use scale efficiency
effectively and it is also a fact that scale inefficiency is increasing every
year.
On the other hand, our results with an output oriented model show similar results
with respect to universities with CRS characteristics having decreased by the same
amount, from 39 to 29, and those with IRS have increased from 9 to 22, however
the number of universities with DRS have decreased from 5 to 2, within the same
period. Likewise, there are 20 universities showing CRS, 2 universities showing IRS
and one DRS year after another within this period, and universities in this model
were not able to use scale efficiency as well. Since output oriented model deals with
maximization of outputs, the number of IRS characteristics is higher as expected.

References

  • Ahn, T., 1987. Efficiency Related Issues in Higher Education: A Data Envelopment Analysis Approach, Ph.D. Thesis, The University of Texas at Austin.
  • Arcelus, F.J. and D.R. Coleman., 1995. “An Efficiency Review of University Departments,” Faculty of Administration, University of New Brunswick, mimeographed.
  • Athanassopoulos, A., Shale, Estelle., 1997. Assessing the comparative efficiency of higher education institutions in the UK by means of data envelopment analysis. Education Eco- nomics,5(2), 117–134.
  • Avkiran, Necmi K., 2001. Investigating technical and scale efficiencies of Australian Uni- versities through Data Envelopment Analysis. Socio-Economic PlanningSciences. 35, 57- 80.
  • Babacan, Adem, 2006. Türkiye’deki Üniversitelerde VZA Yöntemiyle Verimlilik Analizi. C.Ü. Sosyal Bilimler Enstitüsü. Doktora Tezi.
  • Chaparro F. Jimenez J, Smith P., 1997. On the Role of Weight Restrictions in Data Envel- opment Analysis. Journal of Productivity Analysis.8:215-230.
  • Coelli, Tim., 1996. Assessing the performance of Australian universities using data envel- opment analysis. Mimeo. Center for Efficiency and Productivity Analysis, University of New England
  • Cooper W.W, L.M Seiford, K. Tone., 1999. Data Envelopment Analysis. Kluwer Academic Publishers
  • Cooper W.W, L.M Seiford, J.Zhu, 2004. Handbook on Data Envelopment Analysis. Kluwer Academic Publishers
  • Dundar H, Darrell R. Lewis., 1995, Departmental productivity in American universities: Economies of scale and scope Economics of Education Review V.14, 2 P.119-144
  • Forsund Finn R.; Nikias Sarafoglou, 2002.On the Origins of Data Envelopment Analysis. Journal of Productivity Analysis, 17, 23–40.
  • Geraint Johnes, Jill Johnes , 1993. Measuring the Research Performance of UK Economics Departments: An Application of Data Envelopment Analysis Oxford Economic Papers, New Series, Vol. 45, No. 2, pp. 332-347
  • Jenkins, A.L. , 1991. Using Data Envelope Analysis to Evaluate the Relative Efficiency of Academic Departments, Royal Military College, Kingston, mimeo.
  • Kisaer H, Karabacakoğlu Ç., 2004. Çukurova Üniversitesi Diş Hekimliği Fak. Performans Analizi MPM No:679.
  • Kutlar A. Mahmut Kartal., 2004. Cumhuriyet Üniversitesinin Verimlilik Analizi: Fakülte Düzeyinde VZA Yöntemi ile Bir Uygulama. Kocaeli Üniversitesi Sosyal Bilimler Dergisi (8) 2: 49-79.
  • McMillan, M.L., Debasish D., 1997. The relative efficiencies of Canadian universities: a DEA perspective. Research paper No. 97-4, Department of Economics, University of Alberta.
  • Norman, M. Stoker. B. , 1991. Data Envelopment Analysis: The Assessment of Performance. John Wiley and Sons.
  • Sherman, H.D., 1984. “Data Envelopment Analysis as a New Manegerial Audit Methodology- Test and Evaluation”, Auditing: A Journal of Practice and Theory.
  • Susanne Warning, 2004. Performance Differences in German Higher Education: Empirical Analysis of Strategic Groups. Cetre for European Economic Reasearch. http://www.wiwi.uni-konstanz.de/forschergruppewiwi.
  • Thanassoulis E., 2001. Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with İntegrated Software, Kuluwer Academic Publisher
  • Tomkins, C. and R. Gren., 1988. An Experiment in the Use of Data Envelopment Analysis for Evaluating the Efficiency of UK University Departments of Accounting. Financial Accountability and Management 4: 147- 64.
  • Vassiloglou, M, Giokas, D., 1990. A Study of The Relative Efficiency of Bank Branches: An Application of Data Envelopment Analysis. Journal of Operational Research Society. 41: 591-597
There are 22 citations in total.

Details

Other ID JA84MZ65JT
Journal Section Articles
Authors

Aziz Kutlar This is me

Adem Babacan This is me

Publication Date June 1, 2008
Published in Issue Year 2008 Issue: 15

Cite

APA Kutlar, A., & Babacan, A. (2008). Türkiye’deki Kamu Üniversitelerinde CCR Etkinliği-Ölçek Etkinliği Analizi: DEA Tekniği Uygulaması. Kocaeli Üniversitesi Sosyal Bilimler Dergisi(15), 148-172.

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